Please use this identifier to cite or link to this item:
Title: Language learning from texts: Degrees of intrinsic complexity and their characterizations
Authors: Jain, S. 
Kinber, E.
Wiehagen, R.
Issue Date: 2001
Citation: Jain, S., Kinber, E., Wiehagen, R. (2001). Language learning from texts: Degrees of intrinsic complexity and their characterizations. Journal of Computer and System Sciences 63 (3) : 305-354. ScholarBank@NUS Repository.
Abstract: This paper deals with two problems: (1) what makes languages learnable in the limit by natural strategies of varying hardness, and (2) what makes classes of languages the hardest ones to lear. To quantify hardness of learning, we use intrinsic complexity based on reductions between learning problems. Two types of reductions are considered: weak reductions mapping texts (representations of languages) to texts and strong reductions mapping languages to languages. For both types of reductions, characterizations of complete (hardest) classes in terms of their algorithmic and topological potentials have been obtained. To characterize the strong complete degree, we discovered a new and natural complete class capable of "coding" any learning problem using density of the set of rational numbers. We have also discovered and characterized rich hierarchies of degrees of complexity based on "core" natural learning problems. The classes in these hierarchies contain "multidimensional" languages, where the information learned from one dimension aids in learning other dimensions. In one formalization of this idea, the grammars learned from the dimensions 1, 2,...,k specify the "subspace" for the dimension k + 1, while the learning strategy for every dimension is predefined. In our other formalization, a "pattern" learned from the dimension k specifies the learning strategy for the dimension k + 1. A number of open problems are discussed.
Source Title: Journal of Computer and System Sciences
ISSN: 00220000
DOI: 10.1006/jcss.2001.1759
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Sep 18, 2020


checked on Sep 18, 2020

Page view(s)

checked on Sep 15, 2020

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.